Mohan G., Sivakumaran B., Sharma P

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Impact of store environment onimpulse buying behavior

Geetha MohanSSN School of Management and Computer Applications, Chennai, India

Bharadhwaj SivakumaranGreat Lakes Institute of Management, Chennai, India

Piyush SharmaDepartment of Management and Marketing, Faculty of Business,

The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong

AbstractPurpose This paper aims to explore the process by which four store environment (music, light,employee, and layout) and two individual characteristics (shopping enjoyment tendency (SET) andimpulse buying tendency (IBT)) influence impulse buying behavior through positive and negativeaffect, and urge to buy impulsively.

Design/methodology/approach The data were obtained using a structured questionnaire from733 respondents in a mall survey conducted in Chennai, South India.

Findings In the structural model tested with AMOS, the authors found that store environmentdrove impulse buying (IB) through positive affect and urge. Results also showed that the personalityvariables (SET and IBT) influenced IB through positive affect and urge. This paper did not findsupport for the relationship between negative affect and urge.

Research limitations/implications Theoretically, the authors add to the list of antecedents ofimpulse buying, and to the outcomes of store environment. From a managerial viewpoint, the authors

suggest that retail managers invest in improving the store environment to increase the level of impulsebuying in their stores. Specifically, they need to focus on enhancing friendliness of store employees,playing appropriate music, designing proper layouts and having well-lit stores to encourage impulsebuying.

Originality/value Prior research studied the elements of the store independently and also itslong-term impact. To the best of the authors knowledge, their research is the first to study the impactof store environment (in conjunction with trait variables) on impulse buying.

Keywords Impulse buying, Positive/negative affect, Retail shoppers, Store environment,Urge, Retailing,Retailers, Shopping

Paper type Research paper

IntroductionImpulse buying is a widely prevalent phenomenon around the world. According toCoca Colas CEO Muhtar Kent, more than 70 percent of Cokes sales are due to impulsepurchases (Karmali, 2007). Similarly, a Canadian grocery chain observed that itsprofitability would increase by more than 40 percent if each customer purchased anadditional item on impulse (Babin and Attaway, 2000). Prior research on impulsebuying found its many antecedents, including individual characteristics such asimpulse buying tendency (Weun et al., 1998) and optimum stimulation level (Sharmaet al., 2010a), product category variables such as involvement (Jones et al., 2003), and

The current issue and full text archive of this journal is available at

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Impact of storeenvironment

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Received 4 March 2011Revised 22 June 2011

24 November 20113 February 2012

5 April 2012Accepted 7 April 2012

European Journal of Marketing

Vol. 47 No. 10, 2013

pp. 1711-1732

q Emerald Group Publishing Limited

0309-0566

DOI 10.1108/EJM-03-2011-0110


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situational factors such as time and money availability (Beatty and Ferrell, 1998),in-store advertisements (Zhou and Wong, 2003), in-store signage (Peck and Childers,2006), in-store slack (Stilleyet al., 2010), display (Ghani and Kamal, 2010) and type offood consumed (Mishra et al., 2012).

On the other hand, there is a growing stream of research on store environment,which explores the influence of its various elements on consumer behavior. Forexample, it shows that the perceptions about store employees may influence customersattitudes towards merchandise and service quality (Hu and Jasper, 2006). Similarly,convenience, quality, variety and value lead to positive attitudes towards private labels(Collins-Dodd and Lindley, 2003; Vahie and Paswan, 2006) and store brands (Semeijnet al., 2004).

Store environment may also influence the number of items purchased, store liking,time and money spent (Sherman et al., 1997), perceived quality of merchandise andpatronage (Bakeret al., 1994); sales (Milliman, 1982), product evaluation (Wheatley andChiu, 1977), satisfaction (Bitner, 1990), and store choice (Dardenet al., 1983). However,there is little attention paid to the influence of store environment on impulse buyingdespite its increasing importance in making the retail experience a key differentiator(Hu and Jasper, 2006).

While Sherman et al. (1997) explore the influence of store layout, ambience, andsales personnel on unplanned buying they do not consider impulse buying which isdifferent from unplanned buying (Stern, 1962). Beatty and Ferrell (1998) proposed amodel of impulse buying including some consumer traits (impulse buying tendency,shopping enjoyment tendency) and situational variables (time and money available)but do not include store-level factors. They even ask are impulse buyers morevulnerable to store atmospherics?. Similarly, Baker et al.(2002) study the impact ofstore environment on patronage, but not on impulse buying.

Donovanet al. (1994) show that store atmosphere drove pleasure, time and money

spent. Spieset al.(1997) found that a good layout reduces the information rate, i.e. agood layout helps the consumers find products and information easily, unlike a poorlayout; however, it is not clear to what extent store layout may encourage or inhibitimpulse buying.

Recent research in the domain straddling retail store environment (and itscorrelates) and consumer behavior finds that store environment is positively related tostore trust and leads to more positive evaluations of merchandise (Guenzi et al., 2009).A store perceived high on hedonic attributes provided excitement to shoppers (Ashleyet al., 2010). Customers look for fast and efficient billing systems, visualmerchandizing, and informative signage within the store and prompt staff (Ghoshet al., 2010). Arousal induced by music and aroma results in increased pleasure levels,which in turn positively influences approach behavior, and satisfaction with the

shopping experience (Morrisonet al., 2011). In store marketing has a noticeable effecton visual attention (Chandon et al., 2009).

Moreover, most consumer behavior is a result of both personality and situationalinfluences (Russell and Mehrabian, 1976). While Beatty and Ferrell (1998) considerpersonality variables that influence impulse buying, they do not incorporatesituational influences. This research includes store-level situational influences onimpulse buying in our model. There has been research on a few personality variablesexplaining impulse buying (Rook and Fisher, 1995; Ramanathan and Menon, 2006;

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Baumeister, 2002) and a few individual store-level variables influence on impulsebuying (Peck and Childers, 2006; Spies et al., 1997; Zhou and Wong, 2003).

From the review of past and recent literature, it is clear that there is nocomprehensive model that links both personality and situational variables with

impulse buying. This paper attempts to come out with a comprehensive model thatincorporates both to explain impulse buying, philosophically in line with Russell andMehrabian (1976). Specifically, this paper addresses this major gap in extant literatureby studying the impact of four elements of store environment (music, light, layout, andemployees) along with two individual characteristics (impulse buying tendency andshopping enjoyment tendency) on impulse buying behavior. In line with prior research,we included positive and negative affect (Beatty and Ferrell, 1998), and the urge to buyimpulsively (Dholakia, 2000) as mediators of the influence of store environment andindividual variables on impulse buying behavior.

Conceptual framework and hypotheses

Impulse buying, according to Beatty and Ferrell (1998) is a sudden and immediatepurchase with no pre-shopping intentions either to buy the specific product category orto fulfill a specific buying task, whereas unplanned reminder buying may simply beout of stock reminder buying. Impulse buying is thus a spur-of-the-moment purchasewith little thought (a shopper sees some candy and decides to buy on a sudden urge)while unplanned reminder buying is buying since the shopper forgot to put an item onher list (a shopper sees sugar in the store, remembers she is out of stock and buys it).Thus, our definition taken from Beatty and Ferrell (1998) would include only genuinelyimpulsive purchases. This section proposes a holistic model of impulse buying withfour elements of store environment and two individual characteristics (impulse buyingtendency and shopping enjoyment tendency) as antecedents of impulse buying.

Store environmentStore environment consists of ambient factors such as lighting, scent, and music;design factors such as layout and assortment; and social factors such as the presenceand effectiveness of salespersons (Baker et al., 2002). Layout refers to the way in whichproducts, shopping carts, and aisles are arranged; the size and shape of those items,and the spatial relationships among them. Product assortment is the total set of itemsoffered by a retailer. Social factors refer to the people such as other shoppers andsalespeople (Baker et al., 2002). Other shoppers were not considered in this study asthis factor was not directly under the control of the retailer (unlike all the other factorsthat were considered).

Wardet al.(1992) state that consumers do not perceive a store in piecemeal fashionand it is the total configuration of cues (theGestaltof consumers perceptions of stores)

that influences their responses (Mattila and Wirtz, 2001). However, most prior studiesdo not operationalize store environment as an overall construct and instead explore theinfluence of individual elements of store environment, such as layout and signage (Anget al., 1997), product assortment (Simonson, 1999), ambience, and salespersonavailability (Sharma and Stafford, 2000), music (Dubeand Morin, 2001; Beverland et al.,2006), lighting (Summers and Hebert, 2001), and scent (Mattila and Wirtz, 2001; Chebatand Michon, 2003). While Baker et al. (2002) include multiple cues (employee, designand music perceptions) in a single study, they too study only the individual impact of


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these variables and not the overall effect of store environment. Therefore, this paperdefines store environment as a perception of the combination of its elements namelymusic, lighting, layout and employees. We consider its overall impact on customerperceptions and behavior.

Positive and negative affectAffect is a valenced feeling state characterized by its two orthogonal dimensions,namely positive and negative affect (Watsonet al., 1988). Shermanet al.(1997) suggestthat cognition affects store choice whereas emotion affects unplanned purchases.Emotions produced in-store relate with unplanned buying (Donovan et al., 1994) andimpulse buying (Rook, 1987). Shoppers come to stores with specific goals and affectivereactions occur as they work towards meeting such goals (Machleit and Eroglu, 2000).In this paper, we only consider the affect induced in response to the various elements ofthe store environment and not the pre- or post-shopping affective states.

Positive affect represents the extent to which a person may feel enthusiastic, active,

and alert (Beatty and Ferrell, 1998, p. 172). High positive affect is a state of high energy,full concentration, and pleasant engagement whereas low positive affect may consist ofsadness and lethargy (Watsonet al., 1988). In contrast, negative affect involves a feelingof distress and non-pleasurable engagement that subsumes a variety of aversiveaffective states, such as anger, disgust, guilt, fear, and irritation (Watson et al., 1988).

Store environment and positive affectShoppers respond to music psychologically and behaviorally (Yalch and Spangenberg,1990). Music is an important, frequently and commonly studied variable thatinfluences affective states (Bruner, 1990). It is a key ambient variable (Bitner, 1992)shaping consumer behavior in retail environments (Milliman, 1982; 1986; Yalch and

Spangenberg, 1990). The presence of pleasant music produces positive affect (Garlinand Owen, 2006). Well-designed lighting systems can bring an added dimension to aninterior, guide the customers eyes to key sales points, create an atmosphere ofexcitement and induce positive affect (Smith, 1989). Lighting and music together evokepositive affect (Yoo et al., 1998).

Positive experiences arise if the store makes it easy for the consumers to find theproduct they are looking for, by providing a logical store layout and sufficient signage(Bitner, 1992; Spies et al., 1997). Retail layouts are important since they help presentproduct assortments in an effective and positive way (Aghazadeh, 2005). A good layoutmay produce and enhance positive affect by helping the shoppers find what they wantfaster (Spieset al., 1997). A good layout may also make the shopping more enjoyable,by reducing the perceived stress in shopping (Baker et al., 2002) and by evoking

positive affect (Yoo et al., 1998).Store personnel contribute to entertaining store experiences (Jones, 1999). Employee

responses can significantly influence important consumer responses (Bitner, 1990).Often, subtle aspects in the personnels behavior contribute to positive feelings, forexample a smile or being easily available for consumers. Even in brief and mundaneencounters the employee induces positive affect (Mattila and Enz, 2002). Retail stimulibiases affect evaluation in an affect-congruent direction (Gardner, 1985). Based on theabove discussion, we posit:

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H1. Higher evaluations of store environment lead to higher levels of positiveaffect.

Store environment and negative affect

Loud music is one of the major irritants of shopping (dAstous, 2000). Improper or loudmusic may cause physical discomfort (Bitner, 1992) and may induce negative affect. Inattempting to create an appropriate (i.e. soft lighting) atmosphere, management mayadopt a lighting scheme that inhibits shoppers from examining the merchandise,inducing negative affect. Improper illumination levels reduce visual acuity that isneeded to complete environmental tasks (Areni and Kim, 1994). Cluttered shelves,narrow and irregular aisles may increase consumers perception of crowding, which inturn may lead to negative affect. A poor layout causes negative affect (Spieset al., 1997;

Jones, 1999).At the retail outlet, affect is induced by the salesperson (Gardner, 1985; Yoo et al.,

1998). A salespersons actions and behaviors can influence customer satisfaction withhim/her as well as the retailer (Oliver and Swan, 1989) and customer satisfaction has anaffective basis (Westbrook and Oliver, 1991). This linkage occurs, at least in part,because the salesperson and selling firm are often indistinguishable in the mind of theshopper (Crosbyet al., 1990). In fact, absence of salespersons or bad salesmanship mayalso cause negative affect (Jones, 1999). This leads to:

H2. Lower evaluations of store environment lead to higher levels of negativeaffect.

Store environment and urge to buy impulsively (urge)Urge to buy impulsively (urge) is a state of desire that is experienced uponencountering an object in the shopping environment such as a specific product, modelor brand (Rook, 1987; Dholakia, 2000). It is spontaneous, sudden and clearly precedes

the actual impulse action (Beatty and Ferrell, 1998). As consumers browse around in astore, they experience more and more urges, and their likelihood of engaging in animpulse purchase increases (Beatty and Ferrell, 1998).

Music is an important non-verbal communication, generally used to enhance storeatmosphere and sometimes it may induce unplanned (Turley and Milliman, 2000) andeven impulse buying (Mattila and Wirtz, 2001). Music makes people stay longer, spendmore time and money than normal (Milliman, 1982; 1986); hence it is likely that some ofthis spending may be unplanned and possibly result in impulse buying. In fact, musicand lighting are important triggers that create an urge to purchase impulsively (Erogluand Machleit, 1993).

Good lighting techniques help create the right ambience (as in a restaurant). A storewith appropriate lighting may entice shoppers to experience the store and create an

urge to purchase. Well-designed lighting systems can bring an added dimension to aninterior, guide the customers eyes to key sales points, create an atmosphere ofexcitement, induce positive affect, or simply make key approach areas safe and visible(Smith, 1989). Ambient factors including music and lighting have a positive effect onarousal (Sherman et al., 1997) and all these can trigger a desire (urge) to purchaseimpulsively (Eroglu and Machleit, 1993).

An optimal layout gives the ability to facilitate the access to information and aidsthe shopper in decision-making. Peg boards and end caps induce urge to buy


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impulsively (Aghazadeh, 2005). A good layout makes even the utilitarian shopper buyadditionally by creating an urge in them (Sherman et al., 1997). Salespersons can guidethe consumer to explore the store and the product range, thereby inducing the urge tobuy impulsively. Hence:

H3. Higher evaluations of store environment lead to higher levels of urge to buyimpulsively.

Shopping enjoyment tendency and positive affectShopping enjoyment tendency is defined as the pleasure one obtains in the shoppingprocess (Beatty and Ferrell, 1998). Shoppers derive joy and pleasure from shopping(Babinet al., 1994). People shop for both hedonic and utilitarian reasons (Jones, 1999),Consumers who enjoy shopping engage more in non-planned purchases, and getpsychological rewards from the shopping process per se (Bellenger and Korgaonkar,1980). Based on the above and in line with Beatty and Ferrell (1998), we hypothesize:

H4. Higher levels of shopping enjoyment tendency lead to higher levels positiveaffect.

Impulse buying tendency (IBT)Broadly in line with Weun et al.(1998) and Beatty and Ferrell (1998), we define impulsebuying tendency (IBT) as the tendency to make unplanned purchases and to buyspontaneously, with little or no deliberation or consideration of the consequences.Consumers with higher IBT score are more likely to experience impulsive urges and tobuy impulsively in a retail store (Beatty and Ferrell, 1998). Therefore:

H5. Higher levels of impulse buying tendency lead to higher levels of urge to buyimpulsively

Positive affect and urge to buy impulsivelyPrior research shows a positive association between positive affect and impulsebuying. Donovan et al. (1994) found that a pleasant environment contributed to extratime and unplanned shopping. Beatty and Ferrell (1998) also found a positiverelationship between positive affect and urge to buy impulsively. Hence, we posit:

H6. Higher levels of positive affect lead to higher levels of urge to buyimpulsively.

Negative affect and urge to buy impulsivelyIn line with prior research, we assume that positive and negative affect are orthogonalto one another (Watson et al., 1985; Beatty and Ferrell, 1998; Silvera et al., 2008).

The effect of negative effect on impulse buying is ambiguous in the literature. Oneline of research shows that stress reaction (Youn and Faber, 2000) and self-gifting areused to relieve depression (Mick and DeMoss, 1990) i.e. this suggests that negativeaffect would have a positive effect on impulse urges. In a retail setting, negative affectgenerally creates a desire to withdraw from an environment as it makes the consumerperceive the store to be unlikely to solve his/her intended purpose for visiting it (Erogluand Machleit, 1993). Hence, there is little chance of impulsive urges being generated.Moreover, Youn and Faber (2000) talked about pre-existing negative effect (I feel low,

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so will buy something and perk up) and not store-induced affect, which is what we areconcerned with in this paper. Since negative affect may cause withdrawal from thestore, it is unlikely to lead to impulsive urges. Hence, the following:

H7. Higher levels of negative affect lead to lower levels of urge to buy impulsively.

Urge to buy impulsively and impulse buyingFinally, prior research shows that consumers continuously experience impulsive urgesduring their shopping trips as they browse around the stores (Rook, 1987; Beatty andFerrell, 1998), and they are unable to resist many of these impulsive urges despite theirbest efforts to control or regulate them (Dholakia, 2000; Baumeister, 2002). Therefore,as argued earlier, we hypothesize a positive relationship between the urge to buyimpulsively and impulse buying.

H8. Higher levels of urge to buy impulsively lead to higher levels of impulsebuying.

Figure 1 summarizes all the hypotheses.

MethodologySampleWe used a single-stage mall-intercept survey method to collect data using a processsimilar to previous studies (e.g. Beatty and Ferrell, 1998; Sharma et al., 2010a) inChennai, a city in South India. A leading Indian supermarket chain gave us permissionto conduct our survey in its 44 outlets in different shopping locations within Chennai,to provide a fair representation of different segments of shoppers.

A total of 1,478 shoppers were approached out of which 733 agreed to participate inthe study. After removing 13 incomplete questionnaires we had a usable sample of 720

yielding a reasonably high response rate of about 49 percent. The respondents weretold that this survey was a part of a student project from a prestigious university inChennai and possibly this accounts for the good response rate despite not paying anycompensation to the participants. The sample had almost similar proportions of males(52 percent) versus females (48 percent), and married (51 percent) versus unmarried (49percent) participants. The average age was about 30 years and most participants had a

Figure 1Conceptual model (with

hypotheses)


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high school education and above (85 percent), representing occupations such asstudents (26 percent), housewives (19 percent), self-employed (13 percent), employed(39 percent), and retired (3 percent). Overall the sample fairly represents the targetpopulation of urban adult Indian shoppers.

MeasuresWe measured all the independent and mediator variables with multiple-item scales usedin past research (except for lighting) after pre-testing these scales along with severalothers in a series of studies with shoppers. To measure lighting, we adapted items fromthree existing scales. Table I shows all the scale items, their sources, and the relevantdescriptive statistics for each item. First, we measured the dependent variable, impulsepurchases always. Then, we measured store related variables, then the mediators(positive and negative affect and urge) and then the trait variables (IBT, shoppingenjoyment tendency) and then the demographics. After measuring the dependentvariable, impulse purchases, we counterbalanced questions within each category

(e.g. questions pertaining to the store environment, mediators and trait variables).

ProcedureThe interviewers were 20 undergraduate students of a research methodology class whoreceived partial course credit for participation in the project. One of the authors trainedall interviewers on understanding the questionnaire, how to approach the shopper,answering doubts, measuring impulse purchases, how to close the interview and otheraspects of the survey, in line with Beatty and Ferrell (1998).

The interviewer intercepted the shoppers upon their exit from the store andrequested their participation in our survey. Having recorded all the purchases made byeach participant, (s)he asked the shoppers whether each of these purchases wasplanned or unplanned. Out of all the unplanned purchases, the reminder type items

were eliminated by the following question: When you saw this item, were youreminded that you were out of this item and needed it?. Interviewers recorded asimpulse purchases only those that were clearly unplanned and could not be classifiedas reminder items (Beatty and Ferrell, 1998). One of the researchers counted thenumber of such purchases for each shopper to arrive at a total number. Overall, thissurvey found around 16 percent of total purchases to be pure impulse buys while 6.4percent were reminder-based unplanned purchases. Table II shows the frequencydistribution of the total number of impulse purchases by each shopper.

Besides the total number of items bought on impulse we used the proportion ofitems bought on impulse as another operationalization of our dependent variable.However, for data with a wide range of whole numbers log transformations arerecommended (Steel and Torrie, 1980). Moreover, for data using proportions or

percentages, the variance of means tends to be smaller near 0 percent and 100 percentcompared to the means near 30 percent to 70 percent, and arcsine transformation isrecommended to address this concern (Steel and Torrie, 1980). Hence, for a morerigorous analysis, our dependent variable was transformed using log and arcsinetransformations. No major differences in the model fits, the path coefficients, and theirlevels of significance were found.

Since many participants did not buy on impulse (58.5 percent) and only a fewbought more than 3 items on impulse (5.3 percent), we also tested for the impact of

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Scale items

Factorloadings

(l)

Item-totalcorrelation

(a) Mean SD

Music (Morin and Chebat, 2005) 2.63 1.061. The store had pleasant music 0.92 0.56 2.89 1.162. The store had appropriate music 0.92 0.53 2.71 1.093. The store had terrible music

a0.65 0.46 2.30 1.03

Light(Smith, 1989; Areni and Kim, 1994; Summers and Hebert,2001) 3.53 0.681. The store is well lit 0.70 0.49 3.51 0.852. The store is correctly lit (neither too bright nor dull) 0.81 0.54 3.45 0.843. Lighting in the store is pleasant 0.70 0.39 3.64 0.80

Employees(Dickson and Albaum, 1977) 3.56 0.771. The store had knowledgeable employees 0.77 0.62 3.48 0.892. The store had friendly employees 0.87 0.75 3.54 0.88

3. The store had helpful employees 0.87 0.74 3.65 0.89

Layout(Dickson and Albaum, 1977) 3.63 0.741. It was easy to move about in the store 0.75 0.56 3.70 0.822. It was easy to locate products/merchandise in the store 0.83 0.64 3.62 0.853. The store had attractive displays 0.70 0.46 3.57 0.83

Positive affect (Watsonet al., 1988) 3.25 0.721. I felt excited on this shopping trip 0.86 0.66 3.21 0.872. I felt enthusiastic while shopping today 0.87 0.72 3.19 0.863. I felt happy during this shopping trip 0.71 0.54 3.33 0.81

Negative affect (Watsonet al., 1988) 2.32 0.801. I felt bored on this shopping trip 0.85 0.68 2.42 0.93

2. I felt lethargic while shopping today 0.81 0.67 2.34 0.943. I felt upset during this shopping trip 0.87 0.72 2.18 0.91

Urge (Beatty and Ferrell, 1998) 3.06 0.931. I experienced many sudden urges to buy unplanned items 0.80 0.59 3.14 1.042. I was tempted to buy many items that were not on my list 0.79 0.49 3.10 1.043. I experienced no sudden urges to buy unplanned itemsa 0.68 0.44 2.95 1.02

Impulse buying tendency (Weun et al., 1998) 3.12 0.691. I avoid buying things that are not on my shopping lista 0.66 0.44 3.27 0.902. When I go shopping, I buy things that I had not intendedbuying 0.70 0.47 3.10 0.993. I am a person who makes unplanned purchases 0.71 0.48 3.19 0.954. When I see something that really interests me, I buy it

without considering the consequences 0.61 0.40 3.22 0.955. It is fun to buy spontaneously 0.73 0.49 2.83 0.97

Shopping enjoyment tendency, (Sproles and Kendall, 1986) 3.17 0.86Shopping is one of my favorite activities 0.91 0.65 3.60 0.92I find shopping an enjoyable experience 0.89 0.63 3.62 0.88Shopping in stores is a waste of time * 0.67 0.54 2.28 0.92

Note: aItems were reverse coded

Table IScale summary


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outliers on our findings. For this, we eliminated the top 10 percent and the bottom 10percent. We did not find major differences between the fit and the path coefficients that

were originally obtained. We also compared the average scores for all the variables(store environment-related, trait-related, urge-related, affect-related and impulsepurchases-related) and their relationships with each other across different groupsbased on demographic variables and found no major differences. Hence, we do notdiscuss these any further.

Data analysis and findingsMeasurement modelWe used a two-stage structural equation modeling approach with AMOS 17.0, firsttesting the measurement model before analyzing the structural one (Anderson andGerbing, 1988). Based on prior research on reflective versus formative measurementmodels (e.g. Diamantopoulos and Winklhofer, 2001; Jarvis et al., 2003; Coltman et al.,

2008), we treated store environment as a second order formative construct with fourelements (i.e. music, lighting, employees, and layout) as formative indicators since storeenvironment does not exist as an independent entity independent of these four elements;rather, it is a composite measure of these four elements. We treated store environment asa formative second order factor construct since a priori there is no reason to believe thatlighting, music, layout and employees would be correlated with one another and thatthey would be driven by store environment, a second-order factor. Rather, it makes muchmore conceptual sense to think of the perception of store environment being influencedby perceptions of lighting, music, layout and music. This is also consistent with Jarviset al. (2003) who advocate using a formative model under such conditions.

Except for assortment and scent, we obtained excellent reliabilities for allconstructs. Hence, assortment and scent were dropped from further data analysis.After assessing the individual reliability of the constructs, the measurement modelshows a good fit even without adding error covariances (x2 398:68, df137,x2=df2:91, RMSEA 0:051, SRMR 0:063, CFI 0:96) with all the fit indicesbetter than the recommended (RMSEA , 0:06, SRMR , 0:08, CFI . 0:95) cut-offvalues (Hu and Bentler, 1999; Wheaton et al., 1977, p 102).

To test the convergent validity of our measures, we examined the parameterestimates and found them to be large (.0.65) with significantly larget-values (15.9 to23.8) (Anderson and Gerbing, 1988) with high values of item-to-total correlations (0.40

Number of impulse purchasesFrequency

(number of participants) Percentage Cumulative percentage

0 421 58.5 58.5

1 175 24.3 82.82 54 7.5 90.33 32 4.4 94.74 15 2.1 96.85 11 1.5 98.36 6 0.8 99.27 2 0.3 99.48 4 0.6 100.0Total 720 100.0

Table II.Frequency distribution ofimpulse purchases

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to 0.72) and average variance extracted (0.47 to 0.71) showing high convergent validity(Fornell and Larcker, 1981). All the measures also show discriminant validity as theaverage variance extracted in each factor exceeds the square of its correlations with allthe other constructs (Fornell and Larcker, 1981).

Common method varianceSince this study uses the predictor and criterion variables from the same source in asingle survey, we took several precautions to minimize the impact of common methodvariance (CMV). Specifically, we did not collect any personal information from theparticipants to reduce socially desirable responding and evaluation apprehension byensuring the anonymity of the responses. The survey also used a Likert format for theindependent variables and directly calculated the value of the dependent variable,reducing method bias due to the commonalities in scale endpoints and anchoringeffects (Podsakoffet al., 2003).

Using the above procedural remedies helped us minimize CMV in this study but it

may not have been eliminated completely. It is also difficult to identify its exactsource(s). Although Harmans (1967) single-factor test is a popular choice to addressthis, it is an insensitive test, which is likely to under-identify the sources of CMV andit may not control (or partial out) method effects (Podsakoff et al. 2003). Hence, toestimate the method biases at the measurement level and to control the measurementerror, we used the single common method factor approach (Podsakoffet al., 2003).

Specifically, we compared the fit indices between our original measurement modeland one in which all the items loaded on a latent CMV factor besides their theoreticalconstructs. This method allows the partitioning of the variance of responses to a specificmeasure into three components: trait, method, and random error. The model with theCMV factor showed a poor fit (x2 879:13, df166,x2=df 5:29, RMSEA 0:092,SRMR 0:181, CFI 0:77), and a significantly higher x2 value compared to the

original measurement model (Dx2

480:45, Ddf 29, p , 0:001). Hence, most of thevariance in this data is explained by the individual constructs and common methodvariance does not seem to be a significant problem in this study (Podsakoffet al., 2003).

Structural modelThe structural model had a good fit ( x2 388:52, df155, x2=df2:51,RMSEA 0:045, SRMR 0:056, CFI 0:95) with all the fit-indices better than therecommended cut-off values (RMSEA , 0:06, SRMR , 0:08, CFI . 0:95). Due to thedependency of the x2 statistic on the sample size, a higher than cut-off value ofcomparative fit index (CFI) and a value of the x2/df less than three indicate a good fit(Kline, 1998). Other fit indices (NFI 0:94, AGFI 0:92) are also high, showing agood fit. The analysis revealed support for all our hypotheses except for the effect of

negative affect on urge (H7), as summarized in Table III.Specifically, the results indicated that the overall perception of store environment

exerts a significant positive effect on positive affect (b 0:31, p , 0:01) and has asignificant negative influence on negative affect (b 20:29,p , 0:01), supportingH1and H2, respectively. In addition, overall perception of store environment has apositive effect on the urge to buy impulsively (b 0:15, p , 0:05), supporting H3.Moreover, shopping enjoyment tendency has a positive effect on positive affect(b 0:11,p , 0:05) and impulse buying tendency has a positive impact on the urge to


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buy impulsively (b 0:45, p , 0:01), thus supporting H4 and H5, respectively.Positive affect has a positive influence on the urge to buy impulsively (b 0:27;p , 0:05), supporting H6. However, the effect of negative affect on urge to buyimpulsively is not significant (b 20:01;p . 0:10); thusH7is not supported. Finally,as expected, the urge to buy impulsively has a positive effect on impulse buying

(b 0:27; p , 0:01), supportingH8.Test of urge as a mediator. We tested the mediating role of urge using the method

proposed by Iacobucci et al. (2007, p. 152) by first testing a model with a direct pathfrom store environment, positive affect, and negative affect to impulse buying, and an

indirect path via urge. This model also showed a good fit (x2 405:50, df152,x2=df2:67, RMSEA 0:048, SRMR 0:059, CFI 0:94). None of the pathcoefficients for the direct effects are significant, whereas those for the indirect effects

are all significant (as shown in Figure 2). Hence, there is evidence of some mediation

(Iacobucci et al., 2007).Next, we explicitly tested the relative sizes of the indirect (mediated) versus direct

paths by calculating the z-value using the formula z a*b=b 2 s2a a2 s2b

1=2,

Hypotheses Path coefficient t-value Result

H1. Store environment perception! Positive affect 0.31 * * 5.23 SupportedH2.Store environment perception! Negative affect 20.29 * * 23.28 Supported

H3. Store environment perception!Urge to buyimpulsively 0.15 * 2.89 Supported

H4. Shopping enjoyment tendency! Positive affect 0.11 * 2.60 SupportedH5. Impulse buying tendency!Urge to buyimpulsively 0.45 * * 6.98 Supported

H6. Positive affect!Urge to buy impulsively 0.27 * * 3.17 SupportedH7. Negative affect!Urge to buy impulsively 20.01 20.22 Not SupportedH8. Urge to buy impulsively! Impulse buying 0.27 * * 3.21 Supported

Notes: *p , 0:01; * *p , 0:001Table III.Hypotheses and results

Figure 2.Structural model (withdirect and indirect effects)

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where a ( 0.16) is the unstandardized regression coefficient for the associationbetween the independent variable (IV; in this case store environment) and the mediator(urge), and sa ( 0.05) is the standard error of a. Similarly, b ( .30) is theunstandardized regression coefficient for the association between the mediator (urge)

and the dependent variable (DV; here, impulse buying) when the independent variable(store environment) is also included as a predictor in the model. Sb ( 0.07) is thestandard error ofb. Using the above formula, a significantz-value (2.56,p , 0:01) wasobtained, which means that the indirect effect of the IV (store environment) on the DV(impulse buying) via the mediator (urge) is significantly different from zero. Thesefindings support a full-mediation model (Iacobucci et al. 2007).

The correlations matrix of all possible pair-wise inter-correlations of all thevariables in the model (Table IV) also supports the relative superiority of the mediatedvis-a-vis non-mediated or partially mediated models. Specifically, the correlations formusic, light, employees, and layout with urge (0.16, 0.20, 0.21, and 0.02 respectively) arestronger than those with impulse buying (0.03, 0.04, 0.00, and 20.02 respectively).Moreover, urge and impulse buying are also positively correlated (0.14). Hence, the fourelements of store environment seem to have a stronger and direct influence on urge,which in turn has a positive effect on impulse buying, as confirmed in our mediationanalysis as well. When the model was re-run without urge, its fit was poor. This showsthat it is important to have urge in the model, as also recommended by Beatty andFerrell (1998).

DiscussionData analysis found a good fit for our model and obtained support for all hypothesesexcept one. Specifically, it was found that store environment drives impulse buyingbehavior through impulsive urge. However, we did not find any influence of negativeaffect on the urge to buy impulsively; the reason for this in explained in a separate

sub-section.Our research makes a number of theoretical contributions. Sherman et al. (1997)

explored the influence of store layout, ambience, and sales personnel on unplannedbuying but not on impulse buying which is different from unplanned buying (Stern,1962). While Beatty and Ferrell (1998) came up with a model that explains impulsebuying, they did not consider store level variables. It is important to do so since a veryhigh percentage of shopping decisions are taken in the store (Peck and Childers, 2006;Underhill, 1999; Zhou and Wong, 2003). According to Coca Colas CEO Muhthar Kent,the point of sale (store) is critical as more than seventy percent of Cokes sales is basedon impulse purchases (Karmali, 2007). A Canadian grocery chain exploring theavenues for increasing profitability had observed that if each customer purchased oneadditional item, profitability would increase by more than 40 percent (Babin and

Attaway, 2000). Hence, by extending Beatty and Ferrell (1998) in this manner, ourresearch makes an important contribution to the literature. Our study thus addressesthis major gap in the extant literature by studying the impact of four elements of storeenvironment (i.e. music, light, layout, and employees) along with two individualcharacteristics (i.e. impulse buying tendency and shopping enjoyment tendency) onimpulse buying behavior. Earlier studies have considered the various storeenvironment variables on the shoppers behavior independently, but have not takenthe Gestalt approach. In sum, this paper offers a comprehensive model of impulse


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AVE

Music

Light

Employee

Layout

Store

environment

perception

Positive

affect

Negative

affect

Urge

IBT

Shop

Enjoyment

IB(Nos.)

Music

0.7

1

0.8

6

Light

0.5

5

0.1

3**

0.7

1

Employees

0.7

0

0.2

3***

0.2

8***

0.8

3

Layout

0.5

8

0.2

1**

0.3

1***

0.2

8***

0.8

6

Store

environment

perception

N/A

0.6

9***

0.5

7***

0.6

5***

0.6

3***

N/A

Positiveaffect

0.6

7

0.1

7**

0.0

7

0.2

5***

0.1

4**

0.2

4***

0.7

6

Negativeaffect

0.7

1

20.0

9*

20.1

2**

20.2

0***2

0.1

5**

20.2

0***

20.2

1**

0.7

8

Urge

0.5

8

0.1

6**

0.2

0**

0.2

1***

0.0

2

0.2

0***

0.2

4***

20.0

4

0.7

0

Impulsebuying

tendency

0.4

7

0.1

1**

0.1

2**

0.1

3**

0.0

0

0.1

3**

0.1

8**

0.0

2

0.3

6***

0.7

4

Shopping

enjoyment

tendency

0.6

9

0.1

5**

0.1

5**

0.1

8**

0.2

6***

0.2

8***

0.2

4***

20.1

2**

0.1

7**

0.1

6**

0.8

0

Impulsebuying

(numberof

items)

N/A

0.0

3

0.0

4

0.0

0

2

0.0

2

0.0

2

0.0

1

0.0

0

0.1

2**

0.0

7*

0.0

2

N/A

Impulsebuying

(proportion)

N/A

0.0

3

0.0

1

20.0

1

2

0.1

1**

20.0

3

0.0

2

0.0

1

0.1

3**

0.1

3**

0.0

9*

0.1

8***

Notes:Compositereliabilitiesforallthescalesarereportedonthediagonal;AVE,averagevarianceextracted;

*p

,

0:

05;

**p

,

0:

01;*

**p

,

0:

001

Table IV.Correlations matrix

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buying including individual characteristics as well as store environment, consistentwith Russell and Mehrabian (1976) Another aspect that is new in this model is thatstore environment is not just a standard second order construct, but as a formative one,in line with the recommendations of Jarvis et al. (2003).

Likewise, we extend Baker et al. (2002) by showing that store environmentinfluences not only patronage but also impulse buying. Moreover, extant literatureshows the long term effects of store environment such as store choice (Darden et al.,1983), whereas this research shows that it has immediate and spontaneous behavior onimmediate and spontaneous effects such as impulsive buying. It also adds to thefindings of Donovan et al. (1994) and Spies et al. (1997) by showing that storeenvironment affects not just unplanned purchasing (which may be due to more in-storesearching or developing an affect-based liking to a product), but pure impulse buyingas well, which is a result of spontaneous impulsive urges.

Lack of support forH7. We did not find support for H7, i.e. negative affect did notaffect urge to buy impulsively negatively. Beatty and Ferrell (1998) also did not find asignificant influence of negative affect on urge to buy impulsively. The reason for thiscould be that shoppers could not distinguish clearly between pre-existing negativeaffect that may possibly lead to higher impulse buying (e.g. Youn and Faber, 2000), andnegative that arises as a result of a poor shopping trip that should lead to lesserimpulsive buying. Measurement of affect is fraught with problems in survey research;hence further research using alternate methods to measure affect may clarify the effectof negative affect.

Managerial implicationsThis research also has many important managerial implications. First, the resultsfound that roughly 16 percent of shoppers purchases were on impulse in our study.This shows that at least in our sample of Indian shoppers, we found that impulse

buying was prevalent, though not to the extent that it is in other (especially Western)countries. Since the results were obtained in India, we believe that the results aregeneralizable to most other countries, especially Western ones. This is because in India,most stores are small, by Western standards. Most stores have an area of only 2,000square feet or so. This means that aisles are cramped. There are frequent poweroutages, leading to air conditioning being turned off, there are only a few check-outcounters and so on. If impulse buying is generated here because of store environment,it surely ought to be engendered in other countries where stores are larger and nicerwith a better ambience. Finally, impulse buying is considered normatively wrong andis likely to be understated, especially in a collectivist country like India (Kacen and Lee,2002; Tuyet Mai et al., 2003). Thus, ours is a conservative test.

We calculated direct, indirect and total effects of all variables on impulse buying.

For instance, from the path coefficients in Figure 2, the total effect of light on IB was0.029 (i.e. (0.2*0.32*0.02) (0.2*0.16*0.3) (0.2*0.32*0.25*0.3) (0.2*0.08) (0.2* 20.27*0.06) (0.2* 2 0.27* 2 0.03*0.3) 0.029)). All these effects are reported inTable V.

We found that among all the store environment elements, layout had the highesteffect on impulsive buying. This is an interesting finding because until recently mostIndian retail outlets tended to be small and cramped with little access for the shoppersto the actual merchandise. However, in recent years the Indian retail sector has seen


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major changes with the emergence of modern retail formats such as supermarkets andshopping malls in urban centers all over the country. Managers should therefore

continue to invest in improving store layouts, as it would allow shoppers to spend moretime in stores and browse the merchandise, which may trigger impulsive urges (Beattyand Ferrell, 1998). Retailers should not ignore other elements like employees, music andlighting since shoppers evaluate the stores environment in Gestaltterms. If budgetsare a constraint, they may focus on layout first.

Interestingly, store environment (0.26) had a much higher effect on impulse buyingthan the personality variables, IBT and SET put together (0.16). This is welcome newsto managers, since all the elements of the store environment are under their control.Anecdotal evidence suggests that most retailers in developing countries try and cutcorners in an effort to cut costs. Many supermarkets, even those owned by big businesshouses, switch off the air-conditioning from time to time, have employees that are atbest indifferent, if not downright discourteous and rude, and have long checkout times

(Sridharan, 2005). However, we show that this cost cutting may be at the cost ofprofitable impulse purchases, and may even have an adverse impact on patronage(Baker et al., 2002) and loyalty (Sirgy and Samli, 1985). Hence, retailers have to paymuch more attention to the store environment and strive to improve its variouselements on an ongoing basis.

In view of the importance of store environment, even traditional mom and popstores have started investing in additional store space and better layouts (BusinessLine, 2008), possibly realizing that by doing so, they would be gaining immediate andprofitable impulse buying, as also long-term loyalty. Big FMCG companies likeHindustan Unilever (the Indian arm of Unilever) are investing in upgrading the storesto give shoppers a better experience. Foreign retailers such as Wal-Mart and Carrefourwho are looking at entering the developing markets may also take note of our findings.

They may be tempted to follow the strategies of some local retailers and cut costs bynot investing enough in the antecedents of store environment. Doing so may mean lossof profitable impulse purchases. Hence, they probably need to also invest in the variouselements of store environment, as the gain due to impulse purchases may well behigher than the costs incurred in doing so.

Just because we did not find support for H7, it does not follow that managers canignore shoppers negative affect. In other words, it does not mean that shoppersnegative affect is unimportant. This is because of two reasons. First, as explained in

Predictor Direct effect Indirect effect Total effect

Light 0.029 0.029Music 20.26 0.02Layout 0.058 0.058Employee 0.012 0.012Store environment perception 0.08 0.065 0.145Shopping enjoyment tendency 0.012 0.012Impulse buying tendency 0.144 0.144Positive affect 0.02 0.08 0.10Negative affect 0.06 20.009 0.051Urge 0.30 0.30

Table V.Direct and indirect effectson impulse buying

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the discussion section, this result may be an artifact of our (like Beatty and Ferrell,1998) not being to disentangle pre-existing negative affect from store-induced negativeaffect. Second, even if there is no significant negative relationship between negativeaffect and impulse buying, there is clearly a negative relationship between negative

affect and patronage and loyalty (Huddlestonet al., 2004). Hence, retailers must ensurethat their strategies do not lead to shoppers negative affect.

Limitations and future researchWhile our research has valuable contributions, it also has some limitations. First, it didnot consider the effect of other individual characteristics such as self-monitoring,which may affect impulse buying and in-store browsing (Luo, 2005; Sharma et al.,2010a, b). Second, we used a survey design with elements of store environment assituational variables. Future research may use experimental design to manipulatevarious environmental cues and study their impact on real impulse buying behavior,and study the impact of other situational variables on impulse buying such as in-store

browsing and type of shopping trip.Third, we do not consider the aesthetics and appearance of a store, and the role of

in-store promotions, which may also affect impulse buying. Fourth, due to operationalconstraints, our research used grocery shopping as a setting for our study, and foundsignificant results despite a relatively lower degree of impulse buying in this category.Future research may explore the influence of store environment in others retailcategories such as personal products, apparel, accessories, and personal electronics(Joneset al., 2003)

Finally, recent research links impulse buying to another hedonic purchase behavior,namely variety seeking behavior, showing that both these behaviors have a lot incommon, including some antecedents (e.g. consumer impulsiveness and optimumstimulation level) driving both impulse buying as well as variety seeking (Sharmaet al.

2010a, b). If so, given that store environment drives impulse buying, could it drivevariety seeking behavior as well? Future research could address this issue as well.

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About the authorsDr Geetha Mohan is an Assistant Professor at the SSN College of Engineering, Chennai, India.

She earned her PhD in Marketing at the Indian Institute of Technology, Madras. Her researchinterests include impulse buying and variety seeking behaviors. She has presented her researchin major international conferences such as the Asia-Pacific Association for Consumer ResearchConference at ISB Hyderabad in January 2009. Geetha Mohan is the corresponding author andcan be contacted at: [email protected]

Professor Bharadhwaj Sivakumaran is a Professor of Marketing at the Great Lakes Instituteof Management, Chennai, India. He earned his PhD in Marketing at the University of Maryland,USA. His research interests include variety seeking and impulse buying behavior, considerationsets, order of entry, cross-cultural differences in consumer behavior and consumer promotions.He has published his research in Journal of Business Research, Journal of Marketing

Management, and Journal of International Consumer Marketing, among others.Dr Piyush Sharma is an Associate Professor in the Department of Management and

Marketing at The Hong Kong Polytechnic University, Hong Kong. He earned his PhD in

Marketing at Nanyang Technological University, Singapore. His research interests includeself-regulation and self-regulatory failure, cross-cultural consumer behavior, and services andinternational marketing. He has published his research inJournal of the Academy of MarketingScience, Journal of International Business Studies, Journal of Service Research, Journal of

Business Research,Journal of Services Marketing,Journal of Marketing Management,Journal ofInternational Consumer Marketing, and Journal of Euromarketing, among others.

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